PLM IoT platforms: complexity and data scale

PLM IoT platforms: complexity and data scale


Manufacturing companies, analysts and software vendors are sharing excitement about huge potential of IoT and connected products. This is a very good news – I love the idea of things getting connected and optimized. I wish manufacturing industry will operate as smooth as my Waze navigation system by checking road condition, traffic jams and informing me in a following way – changing route, new ETA is 19:40p, you saved 5 min.


So, I’m dreaming about about product lifecycle management system that can tell me – “there is a better component selection for chosen BoM configuration, you saved 12’300$ in the next production batch“. This is probably still a dream in 2015.

However, dreaming during this Friday morning, made me think about complexity and scale of data problem can be discovered in order to make manufacturing work similar to way Waze navigation system works.

Yesterday, I shared some of my thoughts about how future of IoT – digital twin can crash PLM platforms with the scale of data. I want to continue this discussion with two examples I captured earlier this week during PI Congress event in Boston.

The first example came from Airbus presentation made by Tristan Gegaden, Head of Operation of PLM Harmonization Center. He spoke about leveraging of data in a modern digital environment and scale of data. Below you can see few data points about A350 digital model – 3 million part instances in 30’000 configurable items. This is just a single aircraft model.



The second example came from the Ford presentation made by Gahl Berkooz, Head of Data and Governance, Ford Motor Company. In his presentation he spoke about big data driven PLM systems and Hadoop based data technologies Ford is planning to use for data analytics. The following pictures shows how much data Ford vehicles are generating and comparing it to Google data scale. Actually, Google looks a smaller case of Ford data complexity.



What is my conclusion? I think, there is misalignment between “grand strategies” of future IoT driven PLM environments, digital twins, etc. on one side and data platforms and technologies PLM systems are using today in production. The future data scale of IoT enabled manufacturing products (starting from very complex avionic systems and ending up with connected toothbrushes collecting information about every single person combining it with your health history and adapting your dental insurance rate) can be overwhelming. A note before weekend for PLM IoT architects and technologists. Just my thoughts…

Best, Oleg


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